Loss of functional peroxisomes leads to increased mitochondrial biogenesis and reduced autophagy that preserve mitochondrial function.

Peroxisomes are essential for mitochondrial health, as the absence of peroxisomes leads to altered mitochondria. However, it is unclear whether the changes in mitochondria are a function of preserving cellular function or a response to cellular damage caused by the absence of peroxisomes. To address this, we developed conditional hepatocyte-specific Pex16 deficient (Pex16 KO) mice that develop peroxisome loss and subjected them to a low-protein diet to induce metabolic stress. Loss of PEX16 in hepatocytes led to increased biogenesis of small mitochondria and reduced autophagy flux but with preserved capacity for respiration and ATP capacity. Metabolic stress induced by low protein feeding led to mitochondrial dysfunction in Pex16 KO mice and impaired biogenesis. Activation of PPARα partially corrected these mitochondrial disturbances, despite the absence of peroxisomes. The findings of this study demonstrate that the absence of peroxisomes in hepatocytes results in a concerted effort to preserve mitochondrial function, including increased mitochondrial biogenesis, altered morphology, and modified autophagy activity. Our study underscores the relationship between peroxisomes and mitochondria in regulating the hepatic metabolic responses to nutritional stressors.

Micronutrient status in children aged 6-59 months with severe wasting and/or nutritional edema: implications for nutritional rehabilitation formulations.

Undernutrition remains a global struggle and is associated with almost 45% of deaths in children younger than 5 years. Despite advances in management of severe wasting (though less so for nutritional edema), full and sustained recovery remains elusive. Children with severe wasting and/or nutritional edema (also commonly referred to as severe acute malnutrition and part of the umbrella term "severe malnutrition") continue to have a high mortality rate. This suggests a likely multifactorial etiology that may include micronutrient deficiency. Micronutrients are currently provided in therapeutic foods at levels based on expert opinion, with few supportive studies of high quality having been conducted. This narrative review looks at the knowledge base on micronutrient deficiencies in children aged 6-59 months who have severe wasting and/or nutritional edema, in addition to highlighting areas where further research is warranted (See "Future Directions" section).

Natural language processing and machine learning approaches for food categorization and nutrition quality prediction compared with traditional methods.

BACKGROUND: Food categorization and nutrient profiling are labor intensive, time consuming, and costly tasks, given the number of products and labels in large food composition databases and the dynamic food supply. OBJECTIVES: This study used a pretrained language model and supervised machine learning to automate food category classification and nutrition quality score prediction based on manually coded and validated data, and compared prediction results with models using bag-of-words and structured nutrition facts as inputs for predictions. METHODS: Food product information from University of Toronto Food Label Information and Price Database 2017 (n = 17,448) and University of Toronto Food Label Information and Price Database 2020 (n = 74,445) databases were used. Health Canada's Table of Reference Amounts (TRA) (24 categories and 172 subcategories) was used for food categorization and the Food Standards of Australia and New Zealand (FSANZ) nutrient profiling system was used for nutrition quality score evaluation. TRA categories and FSANZ scores were manually coded and validated by trained nutrition researchers. A modified pretrained sentence-Bidirectional Encoder Representations from Transformers model was used to encode unstructured text from food labels into lower-dimensional vector representations, followed by supervised machine learning algorithms (i.e., elastic net, k-Nearest Neighbors, and XGBoost) for multiclass classification and regression tasks. RESULTS: Pretrained language model representations utilized by the XGBoost multiclass classification algorithm reached overall accuracy scores of 0.98 and 0.96 in predicting food TRA major and subcategories, outperforming bag-of-words methods. For FSANZ score prediction, our proposed method reached a similar prediction accuracy (R2: 0.87 and MSE: 14.4) compared with bag-of-words methods (R2: 0.72-0.84; MSE: 30.3-17.6), whereas structured nutrition facts machine learning model performed the best (R2: 0.98; MSE: 2.5). The pretrained language model had a higher generalizable ability on the external test datasets than bag-of-words methods. CONCLUSIONS: Our automation achieved high accuracy in classifying food categories and predicting nutrition quality scores using text information found on food labels. This approach is effective and generalizable in a dynamic food environment, where large amounts of food label data can be obtained from websites.

Accelerating the Classification of NOVA Food Processing Levels Using a Fine-Tuned Language Model: A Multi-Country Study.

The consumption and availability of ultra-processed foods (UPFs), which are associated with an increased risk of noncommunicable diseases, have increased in most countries. While many countries have or are planning to incorporate UPF recommendations in their national dietary guidelines, the classification of food processing levels relies on expertise-based manual categorization, which is labor-intensive and time-consuming. Our study utilized transformer-based language models to automate the classification of food processing levels according to the NOVA classification system in the Canada, Argentina, and US national food databases. We showed that fine-tuned language models using the ingredient list text found on food labels as inputs achieved a high overall accuracy (F1 score of 0.979) in predicting the food processing levels of Canadian food products, outperforming traditional machine learning models using structured nutrient data and bag-of-words. Most of the food categories reached a prediction accuracy of 0.98 using a fined-tuned language model, especially for predicting processed foods and ultra-processed foods. Our automation strategy was also effective and generalizable for classifying food products in the Argentina and US databases, providing a cost-effective approach for policymakers to monitor and regulate the UPFs in the global food supply.

Nutritional quality and price of plant-based dairy and meat analogs in the Canadian food supply system.

There has been an increased consumer interest and public health emphasis on plant-based protein foods, resulting in a rise in the availability of highly processed plant-based analogs. The objectives of this study were to assess the nutritional quality and the price of plant-based dairy and meat analogs compared to their respective animal-derived products and to examine the association between processing levels and the nutritional quality among these products. Using a branded food composition database, products in cheese, yogurt, milk, and meat categories were examined (n = 3231). Products were categorized as plant-based analogs versus animal-derived products using the ingredient list. Products were examined for their nutrient content, overall nutritional quality using the Food Standards Australia New Zealand nutrient profiling model, price, and processing levels using the NOVA classification. All plant-based analogs had lower protein and higher total carbohydrate, sugar, and fiber content compared to their respective animal-derived products. Compared to their respective animal-derived products, plant-based milk and meat analogs had lower energy, total fat, and saturated fat content; plant-based yogurt and meat analogs had lower sodium content; and all plant-based dairy analogs had lower calcium content. Plant-based cheese and yogurt analogs were more expensive than animal-based products; however, there was no significant difference among milk and meat products. There was no association between processing levels and overall nutritional quality among dairy and meat products. Plant-based analogs may be part of a healthy and affordable diet to reduce the intakes of nutrients of concern; however, additional compositional guidelines and/or labeling may be needed to highlight the differences in the levels of nutrients to encourage.

Rebalancing of mitochondrial homeostasis through an NAD+-SIRT1 pathway preserves intestinal barrier function in severe malnutrition.

BACKGROUND: The intestine of children with severe malnutrition (SM) shows structural and functional changes that are linked to increased infection and mortality. SM dysregulates the tryptophan-kynurenine pathway, which may impact processes such as SIRT1- and mTORC1-mediated autophagy and mitochondrial homeostasis. Using a mouse and organoid model of SM, we studied the repercussions of these dysregulations on malnutrition enteropathy and the protective capacity of maintaining autophagy activity and mitochondrial health. METHODS: SM was induced through feeding male weanling C57BL/6 mice a low protein diet (LPD) for 14-days. Mice were either treated with the NAD+-precursor, nicotinamide; an mTORC1-inhibitor, rapamycin; a SIRT1-activator, resveratrol; or SIRT1-inhibitor, EX-527. Malnutrition enteropathy was induced in enteric organoids through amino-acid deprivation. Features of and pathways to malnutrition enteropathy were examined, including paracellular permeability, nutrient absorption, and autophagic, mitochondrial, and reactive-oxygen-species (ROS) abnormalities. FINDINGS: LPD-feeding and ensuing low-tryptophan availability led to villus atrophy, nutrient malabsorption, and intestinal barrier dysfunction. In LPD-fed mice, nicotinamide-supplementation was linked to SIRT1-mediated activation of mitophagy, which reduced damaged mitochondria, and improved intestinal barrier function. Inhibition of mTORC1 reduced intestinal barrier dysfunction and nutrient malabsorption. Findings were validated and extended using an organoid model, demonstrating that resolution of mitochondrial ROS resolved barrier dysfunction. INTERPRETATION: Malnutrition enteropathy arises from a dysregulation of the SIRT1 and mTORC1 pathways, leading to disrupted autophagy, mitochondrial homeostasis, and ROS. Whether nicotinamide-supplementation in children with SM could ameliorate malnutrition enteropathy should be explored in clinical trials. FUNDING: This work was supported by the Bill and Melinda Gates Foundation, the Sickkids Research Institute, the Canadian Institutes of Health Research, and the University Medical Center Groningen.

Inhibition of mTOR improves malnutrition induced hepatic metabolic dysfunction.

Severe malnutrition accounts for half-a-million deaths annually in children under the age of five. Despite improved WHO guidelines, inpatient mortality remains high and is associated with metabolic dysfunction. Previous studies suggest a correlation between hepatic metabolic dysfunction and impaired autophagy. We aimed to determine the role of mTORC1 inhibition in a murine model of malnutrition-induced hepatic dysfunction. Wild type weanling C57/B6 mice were fed a 18 or 1% protein diet for two weeks. A third low-protein group received daily rapamycin injections, an mTORC1 inhibitor. Hepatic metabolic function was assessed by histology, immunofluorescence, gene expression, metabolomics and protein levels. Low protein-fed mice manifested characteristics of severe malnutrition, including weight loss, hypoalbuminemia, hypoglycemia, hepatic steatosis and cholestasis. Low protein-fed mice had fewer mitochondria and showed signs of impaired mitochondrial function. Rapamycin prevented hepatic steatosis, restored ATP levels and fasted plasma glucose levels compared to untreated mice. This correlated with increased content of LC3-II, and decreased content mitochondrial damage marker, PINK1. We demonstrate that hepatic steatosis and disturbed mitochondrial function in a murine model of severe malnutrition can be partially prevented through inhibition of mTORC1. These findings suggest that stimulation of autophagy could be a novel approach to improve metabolic function in severely malnourished children.

The role of the tryptophan-NAD + pathway in a mouse model of severe malnutrition induced liver dysfunction.

Mortality in children with severe malnutrition is strongly related to signs of metabolic dysfunction, such as hypoglycemia. Lower circulating tryptophan levels in children with severe malnutrition suggest a possible disturbance in the tryptophan-nicotinamide adenine dinucleotide (TRP-NAD+) pathway and subsequently in NAD+ dependent metabolism regulator sirtuin1 (SIRT1). Here we show that severe malnutrition in weanling mice, induced by 2-weeks of low protein diet feeding from weaning, leads to an impaired TRP-NAD+ pathway with decreased NAD+ levels and affects hepatic mitochondrial turnover and function. We demonstrate that stimulating the TRP-NAD+ pathway with NAD+ precursors improves hepatic mitochondrial and overall metabolic function through SIRT1 modulation. Activating SIRT1 is sufficient to induce improvement in metabolic functions. Our findings indicate that modulating the TRP-NAD+ pathway can improve liver metabolic function in a mouse model of severe malnutrition. These results could lead to the development of new interventions for children with severe malnutrition.

Effects of high hydrostatic pressure, ultraviolet light-C, and far-infrared treatments on the digestibility, antioxidant and antihypertensive activity of α-casein.

Alpha-casein is the most important bioactive protein in processing technologies. This study investigated the digestibility, antioxidant and antihypertensive activities of α-casein when treated by high hydrostatic pressure (HPP), ultraviolet light-C (UV-C), and far-infrared radiation (FIR). The in vitro digestibility was modified after treatments, especially after 5min/200MPa HHP treatment. Ultra-performance liquid chromatography-tandem mass spectrometry analysis showed that one 5min/200MPa HHP treatment resulted in the highest yield of peptides. Based on the in vitro gastrointestinal digestion and antioxidant and antihypertensive activity assays, HHP increased the angiotensin converting enzyme inhibitory activity at different levels. The 15min UV-C treatment resulted in the highest antioxidant DPPH radical-scavenging activity, while the 15min UV-C and FIR treatments had higher angiotensin converting enzyme inhibitory and antioxidant activities than those of 5min treatments. This study revealed that HHP, UV-C and FIR treatments increased the antioxidant and antihypertensive activities of α-casein.

Structure and IgE-binding properties of α-casein treated by high hydrostatic pressure, UV-C, and far-IR radiations.

α-Casein was treated by high hydrostatic pressure (HHP), UV-C, or far-IR (FIR). These treatments increased roughness, α-helicity, and ß-turn, but decreased ß-sheet and IgE-binding reactivity. One 5-min cycle at 600-MPa pressure caused maximum α-helicity, ß-turn, and surface hydrophobicity (Ho), but minimum stimulated intestinal fluid from α-casein. UV-C (15min) produced the maximum kurtosis, free sulfhydryl content (FSC), and stimulated intestinal fluid, minimum Ho, R, and simulated gastric fluid. FIR (15min) caused the minimum α-helicity and FSC, but maximum R and ß-sheet. The NMR peaks of the main allergenic characteristics affected were 15-17, 23-26, 40, 53, 59 and 85-88, respectively. Generally, all treatments decreased the allergenicity of α-casein by modifying its morphology, ultrastructure, characteristic domains, and peptides. Based on the stimulated digestion tests, UV-C (15min) was more efficient for lowering α-casein allergenicity, thus decreasing the allergenicity of milk.